Triple

T13921635
Position Surface form Disambiguated ID Type / Status
Subject Apayao E334758 entity
Predicate hasLanguage P15 FINISHED
Object Isnag language E135951 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Isnag language | Statement: [Apayao, hasLanguage, Isnag language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Isnag language
Context triple: [Apayao, hasLanguage, Isnag language]
  • A. Isnag language chosen
    The Isnag language is an Austronesian language spoken by the Isnag people in the northern Cordillera region of Luzon in the Philippines.
  • B. Nyishi language
    The Nyishi language is a Tani (Tibeto-Burman) language spoken primarily by the Nyishi people of Arunachal Pradesh in northeastern India.
  • C. Bafia language
    The Bafia language is a Bantu language spoken primarily by the Bafia people in central Cameroon.
  • D. Bagirmi language
    The Bagirmi language is a Central Sudanic language spoken primarily in Chad by the Bagirmi people, known for its role as a regional lingua franca and its rich oral tradition.
  • E. Ahanta language
    The Ahanta language is a Niger-Congo language spoken by the Ahanta people along the coastal region of southwestern Ghana.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d81c5f739081908bc05b2461f54828 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2aa5c1f481908a9d8786872f08fe completed April 14, 2026, 11:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7ce7c4a788190a1e7619a00ab0c2e completed May 3, 2026, 10:38 p.m.
Created at: April 9, 2026, 10:16 p.m.